US 11,961,231 B2
Method and system for medical image interpretation
Meng-Che Cheng, New Taipei (TW); and Ming-Tzuo Yin, New Taipei (TW)
Assigned to Acer Incorporated, New Taipei (TW)
Filed by Acer Incorporated, New Taipei (TW)
Filed on Jun. 25, 2021, as Appl. No. 17/357,994.
Claims priority of application No. 110119273 (TW), filed on May 27, 2021.
Prior Publication US 2022/0383490 A1, Dec. 1, 2022
Int. Cl. G06T 7/00 (2017.01); G06F 18/213 (2023.01); G06F 18/241 (2023.01); G06N 3/08 (2023.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01)
CPC G06T 7/0012 (2013.01) [G06F 18/213 (2023.01); G06F 18/241 (2023.01); G06N 3/08 (2013.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for medical image interpretation, adapted for a computer device, the method comprising:
providing a medical image to a convolutional neural network model, wherein the convolutional neural network model comprises a feature extraction part, a first classifier, and N second classifiers, wherein N is a positive integer;
generating N feature maps by using the feature extraction part of the convolutional neural network model;
obtaining N symptom interpretation results of N symptoms of a disease based on the N feature maps through the N second classifiers; and
obtaining a disease interpretation result of the disease based on the N feature maps through the first classifier,
wherein one of the N second classifiers outputs one of the N symptom interpretation results only according to part of the N feature maps, and another one of the N second classifiers outputs another of the N symptom interpretation results only according to another part of the N feature maps.